Gradient Evolution-based Support Vector Machine Algorithm for Classification

4th Asia Pacific Conference on Manufacturing Systems; 3rd International Manufacturing Engineering Conference

Zulvia, Ferani E.^1 ; Kuo, R.J.^2

Department of Logistics Engineering, Universitas Pertamina, Teuku Nyak Arief Road, Simprug, Kebayoran Lama, Jakarta, Indonesia^1

Department of Industrial Management, National Taiwan University of Science and Technology, No. 43, Kee-Lung Road, Taipei, Taiwan^2

关键词: Benchmark datasets;    Classification algorithm;    Global optimizer;    Gradient evolution;    Metaheuristic;    Support vector machine algorithm;    SVM algorithm;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/319/1/012062/pdf
DOI  :  10.1088/1757-899X/319/1/012062

来源: IOP

【 摘 要 】

This paper proposes a classification algorithm based on a support vector machine (SVM) and gradient evolution (GE) algorithms. SVM algorithm has been widely used in classification. However, its result is significantly influenced by the parameters. Therefore, this paper aims to propose an improvement of SVM algorithm which can find the best SVMs' parameters automatically. The proposed algorithm employs a GE algorithm to automatically determine the SVMs' parameters. The GE algorithm takes a role as a global optimizer in finding the best parameter which will be used by SVM algorithm. The proposed GE-SVM algorithm is verified using some benchmark datasets and compared with other metaheuristic-based SVM algorithms. The experimental results show that the proposed GE-SVM algorithm obtains better results than other algorithms tested in this paper.